{"id":"W7015637418","doi":"","title":"Surging Global Copper Demand Through 2030 to Benefit Canadian Explorers and Producers","year":2021,"lang":"en","type":"other","venue":"","topic":"Extraction and Separation Processes","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Government (linguistics); Consumption (sociology); Production (economics); Climate change","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001042901,0.0008002582,0.0001762584,0.001640054,0.004310681,0.003718453,0.001204071,0.002090454,0.08543837],"category_scores_gemma":[0.002494681,0.0002178975,0.0005515008,0.002111683,0.001333435,0.001565578,0.002392793,0.001464818,0.01230885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02248154,"about_ca_system_score_gemma":0.1034992,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9146342,"about_ca_topic_score_gemma":0.9657422,"domain_scores_codex":[0.9988406,0.00005155082,0.00001319523,0.00003894545,0.0006334794,0.0004221726],"domain_scores_gemma":[0.9980379,0.00007664791,0.00005003758,0.00006542438,0.001369086,0.0004008995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006114171,0.00005141332,0.001392498,0.000192812,0.00001148978,0.0001862832,0.0003058666,0.001015983,0.001273568,0.06417343,0.8599347,0.07140071],"study_design_scores_gemma":[0.000009916517,0.00001524584,0.002058973,0.0001152892,0.000007659442,0.00004244333,0.001026583,0.0006832241,0.0007444176,0.007002249,0.9882773,0.00001673268],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.009030011,0.001752428,0.002703163,0.03897356,0.001187745,0.00009735439,0.005516739,0.0007564811,0.9399825],"genre_scores_gemma":[0.07297506,0.004903163,0.006563826,0.007637706,0.0002072926,0.0000727961,0.003947678,0.0004106123,0.9032819],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.08543837,"threshold_uncertainty_score":0.2858198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01844139100949782,"score_gpt":0.2559695355550878,"score_spread":0.23752814454559,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}